You can hardcode a cheaper model per app step, but four problems erode the savings: quality drops, model retirements, version drift and missed newer models.
Gemini 4 Argon costs $2/$10 per million tokens until November 30, then doubles to $4/$20. Here's the full pricing breakdown and when it beats cheaper models.
Token prices for Claude are identical on AWS Bedrock and the Anthropic API. Here's where the costs actually diverge, and what to pick for your workload.
A routing-first guide to the best LLM for coding in 2026. Which coding tasks go to which model, cost per task type, and SWE-bench benchmark scores compared.
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Claude Mythos launched at $25/$125 per million tokens in a 50-partner preview; Mythos 5.1 is now $10/$50. What changed, and why it matters even without access.
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DeepSeek V4 Pro costs $1.32/$3.96 per million tokens at peak and $0.66/$1.98 off-peak. Prices, limits and status checked 2026-10-15, with monthly math.
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GPT-5.5 launched at $5/$30 per million tokens, double GPT-5.4. Claude Opus 4.7 sits at $5/$25 with the SWE-Bench lead. Here's what changed for routing.
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How to reduce OpenAI API costs: a 9-step checklist and six fixes, from model choice and caching to Flex, Batch and reasoning effort, with October 2026 prices.
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A practical 15-point checklist for reducing AI API costs in 2026, ordered by savings impact and covering model selection, caching, routing, and compression.
How to calculate AI cost per user and its share of plan price, with GPT-6 and Claude examples, reasoning tokens, caching and a $29 plan. Checked Oct 20, 2026.
saas unit economicsai cost per userllm cost managementsaas margins
What 1,000, 100,000 and 1 million Claude tokens cost in October 2026, for Haiku 5.5, Sonnet 5.5, Opus 5.5 and Fable 5.1, plus caching, batch and worked examples.
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Claude Haiku 5.5 and GPT-6 Luna both list $0.10 input and $0.50 output per million tokens. Where the real costs differ, plus Haiku 4.5 vs GPT-4o-mini today.
Fine-tuning is supposed to make models cheaper to run. In most cases, it costs more once training and engineering time are counted. Here's the break-even math.
Gemini 2.5 Flash costs about a quarter of 2.5 Pro per token. Prices, worked examples, when Pro pays off, and the newer models Google offers new projects.
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We estimate GPT-4o-mini handles 60-70% of production tasks about as well as GPT-4o. Here's the framework for knowing which side your workload falls on.
LLM metrics that lead to action: cost per feature and per successful task, cache hit rate, reasoning token share, quality by model. Checked Oct 16, 2026.
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Six techniques, from prompt compression to output length control, that can take a typical 4,500-token prompt to about 2,100 tokens. Here is how to apply them.
Every step in an agent loop compounds token count. A 20-step agent can cost 50x more than a single call. Here is the math and how to design agents on budget.
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Prompt caching can cut up to 90% of your LLM input costs if your prompts repeat. Here is how it works on both providers, when it helps, and when it doesn't.
Retrieved context alone can cost $12,000 a month at 100,000 RAG calls a day. The four real cost centers, how to filter passages, and what each step costs.
A team spending $5,000 a month on Claude can get to about $2,240 without changing what its product does, and lower by moving simple tasks to Haiku 5.5.
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Embedding costs are the most overlooked line item in AI infrastructure. Even cheap models add up at scale. Five techniques we estimate cut costs 50-80%.
Most founding teams underestimate AI API costs by 5-10x in year one. Here are the rules of thumb, scale projections, and budget mistakes that will cost you.
AWS Bedrock is a managed AI platform inside AWS. PromptUnit cuts your LLM costs per request with two settings and no SDK change. Different tools and jobs.
Helicone logs and explains LLM calls; it has been in maintenance mode since Mintlify acquired it in March 2026. PromptUnit cuts the cost of each request.
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Langfuse is an open-source LLM tracing and evaluation platform. PromptUnit cuts the cost of each request. They do different jobs and often work together.
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LangSmith is LangChain's platform for tracing, evaluating and debugging LLM apps. PromptUnit cuts the cost of each request. Different jobs, often used together.
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Portkey and PromptUnit both sit between your app and AI providers. Portkey gives you control: rules, fallback, logs. PromptUnit cuts the cost of each request.
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LLM cost tracking per request, feature and user: a cost function with cached tokens, per-user SQL, provider spend caps and a tools table checked Oct 16, 2026.
OpenRouter puts hundreds of models behind one key. LiteLLM is a gateway you run yourself. PromptUnit cuts cost per request and runs on your own OpenRouter key.
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The PromptUnit GitHub Action scans your PR diff for expensive models like GPT-4o and Claude Opus, then posts routing savings estimates before the code merges.
Tool use resends definitions on every turn and re-includes results in context. Agent loops compound the cost, and token bills run 3-5x over projections.
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OpenAI, Anthropic, Google, and Groq offer 50% off batch processing for async workloads. Stack it with caching for 75-95% savings. Which tasks can wait?
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Gemma 4 31B hits 89.2% AIME at 855 t/s on one H100, under Apache 2.0. The self-hosting break-even against API providers just dropped. Here is the math.
Groq serves OpenAI's open GPT OSS models at up to about 1,000 tokens per second, from $0.075 per million input tokens. Which workloads to move, with real math.
Early first-party data from PromptUnit's own tests: how often a cheaper model matched the one the app chose in 24 comparisons, what it cost, and the limits.
What defaulting to your flagship model costs beyond the invoice: waiting in dollars, real OpenAI rate limits and model retirements. Checked 2026-10-15.